Online Communication Shifts in the Midst of the Covid-19 Pandemic: A Case Study on Snapchat

Abstract

The Covid-19 pandemic has created large shifts in how people stay connected with each other in lieu of social distancing and isolation measures. More and more, individuals have turned to online communications as a necessary replacement for in-person interaction. Despite this, the research community has little understanding of how online communications have been influenced by the offline impacts of Covid-19. Our work touches upon this topic. Specifically, we study research questions around the impact of Covid-19 on online public and private sharing propensity, its influence on online communication homophily, and correlations between online communication and offline case severity in the United States. To do so, we study the usage patterns of 79 million US-based users on Snapchat, a large, leading mobile multimedia-driven social sharing platform. Our findings suggest that Covid-19 has increased propensity to privately communicate with friends, while decreasing propensity to publicly share content when users are out-and-about. Moreover, online communications have observed a marked decrease in baseline homophily across locations, ages and genders, with relative increases in cross-group communications. Finally, we observe that increased offline positive Covid-19 case severity in US states is associated with widening gaps between across-state and within-state communication increases after the onset of Covid-19, as well as marked declines in public sharing. We hope our findings drive further interest and work on online communication changes during pandemics and other extended times of crisis.

Sunshine with a Chance of Smiles: How Does Weather Impact Sentiment on Social Media?

“…In studying historical weather, we also assume that users are relatively immobile. The timeframe of our study coincides with the COVID-19 pandemic, during which Snapchat users exhibited limited movement (Yang et al 2021). Furthermore, we believe our dataset is large enough to compensate for a small subset of users traveling at any time.…”